Abstract:

In order to compare the differences in terpenoid metabolites between different red beet varieties and further create new red beet germplasm, this study used the UPLC-MS/MS detection platform and MWDB (Metware database) to conduct extensive targeted metabolomic analyses of Russian (red beet) and poinsettia (red beet), and combined statistical analysis methods such as clustering and multivariate statistics to screen differential metabolites. The results showed that a total of 48 terpenoids were detected in the two groups of red beet root samples. There were six categories of sesquiterpenes, monoterpenes, diterpenes, triterpenes, triterpene saponins, and other terpenes, including 13 kinds of sesquiterpenes, 7 kinds of monoterpenes, 13 kinds of diterpenes, 7 kinds of triterpenes, and 7 kinds of triterpene saponins, and blumentol C. 8 differential metabolites were screened out in the two groups of samples, of which 5 were down-regulated, including aucubin and alfalfa-3-O-glucuronide-28-O-rhamnosyl (1, 2)-arabinopyranoside, 6'-O-sinapoyl geniposide, mycoside, and protocurcumol; the upregulated substances were Cis-guai-10-en-4α,11-diol, 6'-O- Glucose aucubin and 6,9-dihydroxy-7-sodium-3-ketone. There were significantly different terpene metabolites in different red beet varieties, which could be used as characteristic metabolites for further analysis.

Key words: red beets, root, terpenes, differential metabolites, metabolomics